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Sensors 2016, 16(9), 1504; doi:10.3390/s16091504

Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter

1
Margento R&D, Gosposvetska cesta 84, Maribor 2000, Slovenia
2
Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, Maribor 2000, Slovenia
*
Author to whom correspondence should be addressed.
Academic Editor: Andreas Hütten
Received: 7 July 2016 / Revised: 2 September 2016 / Accepted: 7 September 2016 / Published: 15 September 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [9447 KB, uploaded 22 September 2016]   |  

Abstract

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. View Full-Text
Keywords: accurate proximity measurement; sensor fusion algorithm; Unscented Kalman Filter; finite element modelling accurate proximity measurement; sensor fusion algorithm; Unscented Kalman Filter; finite element modelling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Chowdhury, A.; Sarjaš, A. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter. Sensors 2016, 16, 1504.

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